QIS INSTITUTE OF TECHNOLOGY
(Approved by AICTE, New Delhi & Affiliated to JNTU, Kakinada)
(AN ISO 9001: 2015 Certified Institution)
Ponduru Road, Vengamukkapalem, Ongole, A.P - 523 272
CSE DEPARTMENT NEWS LETTER
TECHNO-FOCUS 2016-17
July to September
CHIEF EDITOR:
Mr. T.V.Subrahmanyam
HOD
EDITOR:
Mr. V.V. Siva Shankar
Academic coordinator
FACULTY ADVISORS:
Mrs. K. Anusha
Ms. A. Sai Harika
STUDENT MEMBERS:
1. M VIJAYA BHASKAR
REDDY, III/CSE
2. G SWATHI, III/CSE
3. K KALYANI, III/CSE
4. R BHARGAVI, III/CSE
Principal’s Message
I am happy to note that the editorial board brings out newsletter for the period July to September 2016.
It is great to find a considerable number of participants in co-curricular and extracurricular activities
which certainly prove that our staff and students are adequately equipped and possess necessary skill-
sets to bring such laurels to the institution.
Dr. G. Lakshmi Narayana
HOD’s message
Am very happy that our Computer science and engineering is releasing Newsletter. It is a platform to
bring out the hidden talents of students and faculty. The major strength of the department is a team of
well qualified and dedicated faculties who are continuously supporting the students for their academic
excellence. We have arranged several guest lectures and workshops for our 2nd, 3rd and 4th year
students in this semester. The department has already applied for the NBA accreditation. I hope the
NBA committee will be visiting our department in the coming semester. So let us work together for the
achievement of this goal. I would like to thank all my colleagues for their tireless efforts to help the
department progress at a very steady pace.
Mr. T.V.Subrahmanyam
Department of Computer Science and Engineering
The Department of Computer Science & Engineering was started in the year 2008. With an
intake of 60, now total strength of the department is 480. The college conducts the
examinations and the degree is awarded by JNTUK Kakinada. University incorporates latest
developments in Basic Computer Science, Programming, Application development,
Communication, Data mining and warehousing and allied fields in a dynamic fashion so that the
student is exposed to the latest technological advancements during the course of study.
Vision of the Department
To produce highly knowledgeable computer science and engineering professionals comprising
of technical skills & competence to meet the global requirements embedding with research,
ethical values and societal commitment.
Mission of the Department
Impart quality education in computer science and engineering through innovative
teaching and learning methodologies.
Conduct industry ready skill development programs to bridge the gap between
academia and industry to produce competitive software professionals with research and
lifelong learning.
Inculcate team work, ethical values to make them socially committed professionals.
Program Educational Objectives (PEOs)
PEO 1: Graduates will have solid foundation in fundamentals of computer science and
engineering required to solve computing problems and create innovative software products
and solutions for the real life problems.
PEO 2: Graduates will have technical competence and skills to use modern and cost-effective
tools and technologies and have extensive and effective practical skills in computer science and
engineering to pursue a career as a computer engineer.
PEO 3: Graduates will have attributes like professionals with world class academic excellence,
ethics, best practices, values, social concerns, lifelong learning and openness to other
international cultures to meet the global needs.
PEO 4: Graduates will have managerial and entrepreneur skills with cross-cultural etiquettes,
leading to a sustainable competitive edge in R&D and meeting societal needs.
Guest Lecture
A number of Guest Lectures from various Institutional and Industrial Experts in the field were
organized by department OF CSE for in-depth understanding of the subjects. Table shows the
list of some guest lecturers organized.
Date Topic Resource person
12-Sep-16
Software Engineering
RNV Jagan Mohan, Assoc professor, Swarnandhra College of Engineering and Technology, Narsapuram
Workshop
Date Topic Resource person
15/9/2016 to
17/9/2016
Software Testing Tools MR. ABDUL AZEEZ, TEST MANAGER, CAPGEMINI,
HYDERABAD.
6/09/2016
Internet of things
Students Participation in inter-institute events
S.No Name of the student Date Title of the event
College/university & location
1 ANANTHU GURUCHARAN 7-Jul-16
Poster presentation
SV university, Tirupati
2 BHIMANADAM ABHIRAMI REDDY 7-Jul-16
Poster presentation
SV university, Tirupati
3 DHULIPALLA PRABHAKAR 7-Jul-16
Poster presentation
SV university, Tirupati
4
GONDI AVINASH 7-Jul-16 Poster presentation
SV university, Tirupati
5 GUDIVADA VAMSI 7-Jul-16
Poster presentation
SV university, Tirupati
6 IRIGELA BRAHMA REDDY 7-Jul-16
Poster presentation
SV university, Tirupati
7 JAMPALA MANOJ 7-Jul-16
Poster presentation
SV university, Tirupati
students who participated outside a state
S.No Name of the student Date Title of the
event
College/university
& location
1 ADDANKI RAJA RAJESWARI 27-8-16 Grid computing Hindustan university, chennai
2 ANNABATHINA SAI SRAVANI 27-8-16 Grid computing Hindustan university, chennai
3 ARETI SRAVANI 27-8-16 Grid computing Hindustan university, chennai
4 ASI MEENA 27-8-16 Grid computing Hindustan university, chennai
5 ATTULURI LAVANYA 27-8-16 Grid computing Hindustan university, chennai
6 AVULA VENNELA 27-8-16 Grid computing Hindustan university, chennai
7 BALINA TEJASWI 27-8-16 Grid computing Hindustan university, chennai
8 BATHINEEDI ANVITHA 27-8-16 Grid computing Hindustan university, chennai
Placement Training
S.NO Date of the Event
Resource person Details of training Program
6
30.9.2016 Mr.Jishnu AMCAT Orientation
7
22.9.2016 Mr. Praveen ERP Training
8
2.9.2016 Mr.Kirithivasan How to prepare for HR round
9
29.8.2016 Mr.Prasanth Software Technologies used in IT industry
10
19.7.2016 Ms.Garima Workshops on Overseas Education
11
21.7.2016 Mr.Avinash Orientation on CRT
Placements
One Week Training Classes on GIS
PROGRAMS CONDUCTED BY EDC
S.NO Name of the
Resource person
Name of the Event Beneficiary Date of the
Event
1 Mr. D. Krishna Reddy, Relationship Manager, Birla Asset
managenment company Ltd., Vizag
Workshop on Business & Wealth
Management
Students of different years &
different branches
22.07.2016
2 Dr. P. Hari Babu, ANU PG CENTER,
Ongole
Awareness on E-Marketing Registered Students from all
Departments
12.08.2016
3 Dr.N.Venkateswara Rao, ANU PG Center,
Ongole
Women's Role in Indian Economic
Development (International
Womens Day)
Students of different years &
different branches
09.09.2016
Student Achievements & Contributions
Name of the Student Name of the Event Position/Prize Awarded by
G.SAI KRISHNA JNTU-K FOOTBALL INTERCOLLEGIATE
TOURNAMENT CUM SELECTION TRAILS
1 MEMBER SELECTED TO
JNTU-KAKINADA
UNIVERSITY TEAM
JNTU-KAKINADA
M.VIJAYA BASKAR
M.ASHOK
M.V. ABHISHEK
M.NIHAR
T.SAI PRAKASH
N.MOHAN BABU
B.NARESH
U.SAI VINEETH
K.V.S.N. CHARAN
M.ADITHYA
B.HARI KRISHNA
G.RAVINDRA
SK.AABID A.P STATE INTER-DISTRICT SENIOR WUSHU(MEN)
TOURNAMENT
STATE- BRONZE MEDAL
Govt of A.P
Student Selected to National Level Long Jump Competitions
Student Selected to South Jone Competitions
Student Selected to JNTU Hockey Team
Student Winner in Athletics competitions
Celebrations Celebrations of Mokshagundam Visveswaraiah
Technical Articles
Demystifying Machine Learning
Machine Learning”. Now that’s a word that packs a punch! Machine learning is hot
stuff these days! And why won’t it be? Almost every “enticing” new development in
the field of Computer Science and Software Development in general has something
related to machine learning behind the veils. Microsoft’s Cortana – Machine Learning.
Object and Face Recognition – Machine Learning and Computer Vision. Advanced
UX improvement programs – Machine Learning (yes!. The Amazon product
recommendation you just got was the number crunching effort of some Machine
Learning Algorithm).
And not even just that. Machine Learning and Data Science in general is
EVERYWHERE. It is as omnipotent as God himself, had he been into Computers!
Why? Because Data is everywhere!
So it is natural, that anyone who has above average brains and can differentiate
between Programming Paradigms by taking a sneak-peek at Code, is intrigued by
Machine Learning.
But what is Machine Learning? And how big is Machine Learning? Let’s demystify
Machine Learning, once and for all. And to do that, rather than presenting technical
specifications, we’ll follow a “Understand by Example” approach.
Machine Learning : What is it really?
Well, Machine Learning is a subfield of Artificial Intelligence which evolved from
Pattern Recognition and Computational Learning theory. Arthur Lee Samuel defines
Machine Learning as: Field of study that gives computers the ability to learn without
being explicitly programmed.
So, basically, the field of Computer Science and Artificial intelligence that “learns”
from data without human intervention.
But this view has a flaw. As a result of this perception, whenever the word Machine
Learning is thrown around, people usually think of “A.I.” and “Neural Networks that
can mimic Human brains ( as of now, that is not possible)”, Self Driving Cars and
what not. But Machine Learning is far beyond that. Below we uncover some expected
and some generally not expected facets of Modern Computing where Machine
Learning is in action.
Machine Learning: The Expected
We’ll start with some places where you might expect Machine Learning to play a part.
1. Speech Recognition (Natural Language Processing in more technical terms)
: You talk to Cortana on Windows Devices. But how does it understand what you
say? Along comes the field of Natural Language Processing, or N.L.P. It deals
with the study of interactions between Machines and Humans, via Linguistics.
Guess what is at the heart of NLP: Machine Learning Algorithms and Systems (
Hidden Markov Models being one).
2. Computer Vision : Computer Vision is a subfield of AI which deals with a
Machine’s (probable) interpretation of the Real World. In other words, all Facial
Recognition, Pattern Recognition, Character Recognition Techniques belong to
Computer Vision. And Machine Learning once again, with it wide range of
Algorithms, is at the heart of Computer Vision.
3. Google’s Self Driving Car : Well. You can imagine what drives it actually. More
Machine Learning goodness.
But these were expected applications. Even a naysayer would have a good insight about
these feats of technology being brought to life by some “mystical (and extremely
hard) mind crunching Computer wizardry”.
Machine Learning : The Unexpected
Let’s visit some places normal folks would not really associate easily with Machine
Learning:
1. Amazon’s Product Recommendations: Ever wondered how Amazon always has a
recommendation that just tempts you to lighten your wallet. Well, that’s a
Machine Learning Algorithm(s) called “Recommender Systems” working in the
backdrop. It learns every user’s personal preferences and makes recommendations
according to that.
2. Youtube/Netflix : They work just as above!
3. Data Mining / Big Data : This might not be so much of a shock to many. But
Data Mining and Big Data are just manifestations of studying and learning
from data at a larger scale. And wherever there’s the objective of extracting
information from data, you’ll find Machine Learning lurking nearby.
4. Stock Market/Housing Finance/Real Estate : All of these fields, incorporate a lot
of Machine Learning systems in order to better assess the market, namely
“Regression Techniques”, for things as mediocre as predicting the price of a House,
to predicting and analyzing stock market trends.
So as you might have seen now. Machine Learning actually is everywhere. From
Research and Development to improving business of Small Companies. It is
everywhere. And hence it makes up for quite a career option, as the industry is on the
rise and is the boon is not stopping any time soon.
Reinforcement learning
Reinforcement learning is an area of Machine Learning. Reinforcement. It is about
taking suitable action to maximize reward in a particular situation. It is employed by
various software and machines to find the best possible behavior or path it should take
in a specific situation. Reinforcement learning differs from the supervised learning
in a way that in supervised learning the training data has the answer key with it so
the model is trained with the correct answer itself whereas in reinforcement learning,
there is no answer but the reinforcement agent decides what to do to perform the given
task. In the absence of training dataset, it is bound to learn from its experience.
Example : The problem is as follows: We have an agent and a reward, with many
hurdles in between. The agent is supposed to find the best possible path to reach the
reward. The following problem explains the problem more easily.
The above image shows robot, diamond and fire. The goal of the robot is to get the
reward that is the diamond and avoid the hurdles that is fire. The robot learns by
trying all the possible paths and then choosing the path which gives him the reward
with the least hurdles. Each right step will give the robot a reward and each wrong step
will subtract the reward of the robot. The total reward will be calculated when it reaches
the final reward that is the diamond.
Input: The input should be an initial state from which the model will start
Output: There are many possible output as there are variety of solution to a
particular problem
Training: The training is based upon the input, The model will return a state and
the user will decide to reward or punish the model based on its output.
The model keeps continues to learn.
The best solution is decided based on the maximum reward.
Puzzle Corner
Here is a puzzle known as the Covent Garden Problem, which
appeared in London half a century ago, accompanied by the
somewhat surprising assertion that it had mystified the best
mathematicians of England:
Mrs. Smith and Mrs. Jones had equal number of apples but Mrs.
Jones had larger fruits and was selling hers at the rate of two for a
penny, while Mrs. Smith sold three of hers for a penny.
Mrs. Smith was for some reason called away and asked Mrs. Jones
to dispose of her stock. Upon accepting the responsibility of
disposing her friend's stock, Mrs. Jones mixed them together and
sold them of at the rate of five apples for two pence.
When Mrs. Smith returned the next day the apples had all been
disposed of, but when they came to divide the proceeds they found
that they were just seven pence short, and it is this shortage in the apple or financial market which has disturbed the mathematical
equilibrium for such a long period.
Supposing that they divided the money equally, each taking one-half, the problem is to tell just how much money Mrs. Jones lost by
the unfortunate partnership?
Our Solution:
The mixed apples were sold of at the rate of five apples for two pence. So they must have had a
multiple of five i.e. 5, 10, 15, 20, 25, 30, ..., 60, 65, ... etc apples.
But the minimum number of apples they could have together is 60; so that 30 would have been
of Mrs. Smith's that would fetch her 10 (an integer) pence and the other 30 of Mrs. Jones's that
would fetch her 15 (also an integer) pence.
When sold separately it would fetch them 10+15=25 pence altogether. But when sold together it
would fetch them 60X2/5=24 pence i.e. a loss of one (25-24=1) pence.
Since they lost 7 pence altogether; they had altogether 60X7=420 apples that fetched them only
420X2/5=168 pence and they shared 84 pence each of them. But Mrs. Jones could sell her
420/2=210 apples for 210/2=105 pence so she lost "21 pence".
Note: to solve it algebraically:
They lost 7 pence altogether
Suppose each lady has x apples
x/2 + x/3 - 2(2x/5) = 7
15x + 10x - 24x = 210
x = 210
Note: Mrs. Johns lost 21 pence.
But without working Mrs. Smith earned 14 extra pence!
(84 pence − 210/3 pence = 14 pence).
Not very fair!
(Perhaps Mrs. Johns was not very good at math)
.
Address for Correspondence
Principal – Dr. G. Lakshmi Narayana Rao – Cell No. 9246419528
President – Sri N. Nageswara Rao - Cell No: 98492 93405
Executive Chairman/Secretary & Correspondent – Sri. N. Surya Kalyan Chakravarthy – Cell No. 99499 99977
Admission Coordinator – Mr. G. Srinivasa Rao - Cell No.9246419579
QIS INSTITUTE OF TECHNOLOGY
Pondur Road, Vengamukkapalem, Ongole, Prakasham District, A.P -523 272,
Ph: 08592-6 50172, Cell: 9246419528.
www.qisit.edu.in E-mail: [email protected]